Humanoid robot-assisted interventions among children with diabetes: A systematic scoping review

Background: Although the humanoid robot is highly engaging for children, whether humanoid robot-assisted interventions could help in diabetes management is still unclear.

Objectives: This review aimed to elucidate the roles of humanoid robot in managing diabetes and observe the effects of humanoid robot-assisted interventions among children with type I diabetes mellitus.

Methods: Arksey and O'Malley's methodological framework was used to conduct this scoping review.

Data resource: We conducted a comprehensive search in 10 databases, including IEEE Xplore Digital Library, CINAHL, Cochrane Library, EMBASE, PubMed, Scopus, Web of Science, ProQuest, WanFang, and CNKI, from May 1, 1989 to February 1, 2020. The reference lists of key texts were examined and citation chaining was conducted. In addition, our team searched gray literature and relevant journals to maximise the searching.

Review methods: Two independent reviewers examined all full articles for fitness with the eligibility criteria. Items of data extraction included the characteristics of articles, description of intervention, and mechanism of humanoid robot in improving the management of children with diabetes.

Results: A total of 2,755 articles were retrieved, 22 of which were included from five countries across different ethnicities. Five roles of humanoid robots in managing diabetes among children with type I diabetes mellitus were identified: disease manager, educator, advocator, emotional supporter, and communicator. To some extent, effects seem to be related to the positive improvement of affective, experiential, relational, cognitive, and behavioral perspectives from humanoid robot-assisted intervention.

Conclusions: The roles of humanoids have been designed to perform their multidomain functionality. Although many positive effects were observed, the majority of selected articles have methodological issues. Future studies need an improved methodology for large-scale controlled trials.